Triple
T3406146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pingguoyuan station |
E71775
|
entity |
| Predicate | isPublicTransportStation |
P49108
|
FINISHED |
| Object | yes |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: yes | Statement: [Pingguoyuan station, isPublicTransportStation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPublicTransportStation Context triple: [Pingguoyuan station, isPublicTransportStation, yes]
-
A.
hasPublicTransportStop
Indicates that a location or area contains or is served by a public transport stop, such as a bus, tram, or train stop.
-
B.
isPublicTransport
Indicates that the entity functions as a mode or instance of transportation that is available for use by the general public, typically operating on fixed routes or schedules.
-
C.
hasBusStation
Indicates that a place or area contains or is served by a bus station.
-
D.
hasPublicTransitRole
Indicates that an entity holds a specific functional role or responsibility within a public transit system.
-
E.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ad85aac4808190a092c9cc8911f584 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb8ec68c88190913df5f6cafad9e9 |
completed | March 8, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69adadfa73ac8190a163f93e88d217f8 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb21a437c81908bca88d5e123d744 |
completed | March 8, 2026, 5:30 p.m. |
Created at: March 8, 2026, 3:15 p.m.